PhD scholarship in AI-Augmented Sense-Making in Digital Phenotyping - DTU Health Tech

We are looking for an ambitious PhD student to work at the intersection of digital health, artificial intelligence, large language models (LLMs), and human-computer interaction. The PhD project, SCALE – AI-Augmented Sense-Making of Large-Scale Population-Based Digital Phenotyping Datasets, will investigate how LLMs and interactive AI can help researchers explore complex health data collected from smartphones and wearables. The goal is to develop an interactive environment where researchers can use natural language to explore and visualize multimodal data, identify patterns and anomalies, and iteratively develop hypotheses in collaboration with AI. The project will use real-world data from the Copenhagen Research Platform (CARP), including an ongoing nationwide study of cognition and mental health. You will collaborate with researchers at DTU and at Eindhoven University of Technology (TU/e), which hosts a related "sister" PhD project.Responsibilities and tasks Your main responsibility will be to develop and evaluate new methods and interactive technologies for AI-augmented exploration of large-scale digital phenotyping data. You will:

• Study how health researchers explore complex multimodal datasets and identify their analytical needs and workflows.
• Design and implement an LLM-based environment translating natural-language questions into data queries, analyses, and visualizations.
• Investigate human-AI interaction where AI assists in identifying patterns, anomalies, and hypotheses while keeping researchers in control.
• Work with large-scale CARP datasets containing smartphone, wearable, behavioral, physiological, and self-reported data.
• Evaluate the developed methods with researchers, focusing on usability, efficiency, explainability, and trust.
• Collaborate with the sister PhD project at TU/e, including a research stay, joint development, and scientific publications.

Qualifications You must have a two-year master's degree (120 ECTS points) or a similar degree with an academic level equivalent to a two-year master's degree. We are looking for a candidate with:

• A master's degree in computer science, data science, AI, health technology, biomedical engineering, HCI, or a related field.
• Strong programming skills and experience with data science and machine learning.
• Experience with LLMs, generative AI, and AI-supported data analysis.
• Experience in data visualization, human-AI interaction, and explainable AI.
• Interest in working with large, heterogeneous datasets from smartphones and wearables.
• Ability to design and implement research prototypes and conduct empirical evaluations.
• Good communication and scientific writing skills in English and the ability to work in an interdisciplinary, international team.

Experience with digital health, digital phenotyping, time-series analysis, visual analytics, HCI/user studies, or mobile and wearable sensing is an advantage.

• A letter motivating the application (cover letter)
• Curriculum vitae
• Grade transcripts and BSc/MSc diploma (in English) including official description of grading scale
• Links to any online resources, like source code, hardware design, videos, etc.
• A link to a 2-minute (max) video of yourself explaining why you are a fit for the position